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Institution

Government of Canada

GovernmentOttawa, Ontario, Canada
About: Government of Canada is a government organization based out in Ottawa, Ontario, Canada. It is known for research contribution in the topics: Monetary policy & Productivity. The organization has 796 authors who have published 886 publications receiving 21366 citations. The organization is also known as: federal government of Canada & Her Majesty's Government.


Papers
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Journal ArticleDOI
TL;DR: Les auteurs appliquent au systeme canadien de transfert de paiements de grande valeur propose a methode similaire a l'algorithme PageRank de Google as mentioned in this paper.
Abstract: Les auteurs appliquent au systeme canadien de transfert de paiements de grande valeur une methode similaire a l'algorithme PageRank de Google. Ils obtiennent ainsi une estimation de la vitesse de traitement des paiements dans chaque banque.

16 citations

Journal ArticleDOI
TL;DR: A probabilistic framework for remaining useful life (RUL) prediction of bearings that can work without the training data from other bearings and is an unsupervised framework that makes operators free from manual parameters setting and costly tuning runs.
Abstract: This article presents a probabilistic framework for remaining useful life (RUL) prediction of bearings. This framework comprises two phases: 1) early fault detection, i.e., modeling the vibration signal as a series of graphs and then conducting graph spectrum analysis to detect the topological change of graph for early fault detection and 2) RUL prediction, i.e., adopting a probabilistic model for bearing RUL prediction given the detected early fault. Specifically, the least square method and noninformation distribution are employed to set the prior knowledge within this model. Meanwhile, a state-of-the-art Markov chain Monte Carlo method, No-U-Turn sampler, is investigated in posterior sampling for predicting RUL and outputting uncertainty. As a result, this framework can work without the training data from other bearings. Besides, it is an unsupervised framework that makes operators free from manual parameters setting and costly tuning runs. In addition to theoretical derivation, the proposed framework is validated using both synthetic data and real-world data and compared with the representative methods in this field. Excellent results show the effectiveness of this probabilistic framework in the RUL prediction of bearings.

16 citations

Journal ArticleDOI
TL;DR: Results indicate that most bull trout captured immediately downstream from coal mining activity in the region have concentrations of Se that would be expected to impair recruitment, and it is concluded that bull trout populations in Alberta's northeast slopes region are at risk of decline.
Abstract: Selenium (Se) is an essential nutrient, but in higher concentrations can reduce recruitment in fish populations by increasing rates of deformities during early development. Recent work has identified elevated levels of Se in water and biota collected downstream from coal mining activity in Alberta's northeast slopes region. We also recently identified increased incidence of terata and edema in rainbow trout and brook trout with elevated tissue Se from this area. However, there is currently no information regarding the potential for Se to contribute to declining stocks of bull trout, a species of concern in the area. The present study provides an assessment of the potential for Se to contribute to low recruitment in bull trout downstream from coal mining activity. Non-destructive muscle biopsy sampling and a sensitive atomic fluorescence analysis technique are used to determine Se. Results indicate that most bull trout (>90%) captured immediately downstream from coal mining activity in the region have concentrations of Se that would be expected to impair recruitment. Additional work is required to determine the extent of Se's contribution to low recruitment in bull trout.

16 citations

Posted Content
TL;DR: The authors used discrete-choice models to quantify the role of consumer socioeconomic characteristics, payment instrument attributes, and transaction features on the probability of using cash, debit card, or credit card at the point-of-sale.
Abstract: This paper uses discrete-choice models to quantify the role of consumer socioeconomic characteristics, payment instrument attributes, and transaction features on the probability of using cash, debit card, or credit card at the point-of-sale. We use the Bank of Canada 2009 Method of Payment Survey, a two-part survey among adult Canadians containing a detailed questionnaire and a three-day shopping diary. We find that cash is still used intensively at low value transactions due to speed, merchant acceptance, and low costs. Debit and credit cards are used more frequently for higher transaction values where safety, record keeping, the ability to delay payment and credit card rewards gain prominence. We present estimates of the elasticity of using a credit card with respect to credit card rewards. Reward elasticities are a key element in understanding the impact of retail payment pricing regulation on consumer payment instrument usage and welfare.

16 citations

Journal ArticleDOI
TL;DR: In this paper, a method of obtaining MTI's from response surface equations or from tolerance models similar to the toxic units model is presented, which is one of the more attractive approaches for describing and predicting the effects of mixtures of toxicants.
Abstract: The use of Mixture Toxicity Indices (MTI's) is one of the more attractive approaches for describing and predicting the effects of mixtures of toxicants. For an MTI to apply to all possible mixtures of the compounds in question, it must summarize information from a model describing all possible responses of interest. A method of obtaining MTI's from response surface equations or from tolerance models similar to the toxic units model is presented. Methods of calculating several MTI's with desirable properties from multivariable probit response surfaces are demonstrated.

16 citations


Authors

Showing all 802 results

NameH-indexPapersCitations
Kingston H. G. Mills9231329630
David W. Schindler8521739792
Martha C. Anderson7034020288
Hui Li6224614395
Lei Zhang5814621872
Michael J. Vanni5512411714
Cars Hommes5425014984
Richard E. Caves5311524552
John W. M. Rudd51709446
Karen A. Kidd4716310255
Kenneth O. Hill431268842
Steven H. Ferguson432256797
Derwyn C. Johnson411038208
Kevin E. Percy40915167
Guy Ampleman401284706
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20234
20223
202147
202044
201931
201832